Buddha Shrestha, Haeyong Chung, R. S. Aygün
{"title":"FaceTimeMap","authors":"Buddha Shrestha, Haeyong Chung, R. S. Aygün","doi":"10.4018/ijmdem.2019040103","DOIUrl":null,"url":null,"abstract":"In this article, the authors study bitmap indexing for temporal querying of faces that appear in videos.Sincethebitmapindexisoriginallydesignedtoselectasetofrecordsthatsatisfyavalue inthedomainoftheattribute,thereisnoclearstrategyforhowtoapplyitfortemporalquerying. Accordingly,theauthorsintroduceamulti-levelbitmapindexthattheauthorscall“FaceTimeMap” for temporal querying of faces in videos. The first level of the FaceTimeMap index is used for determiningwhetherapersonappearsinavideoornot,whereasthesecondleveloftheindexis usedfordeterminingintervalswhenapersonappears.First,theauthorsanalyzetheco-appearance querywheretwoormorepeopleappearsimultaneouslyinavideo,andthenexaminenext-appearance querywhereapersonappearsrightafteranotherperson.Inaddition,toconsiderthegapbetweenthe appearanceofpeople,theauthorsstudyeventual-andprior-appearancequeries.Queriesaresatisfied byapplyingbitwiseoperationsontheFaceTimeMapindex.Theauthorsprovidesomeperformance studiesassociatedwiththisindex. KEywoRDS Allen’s Intervals, Co-Appearance, Eventual-Appearance, Face Search, Next-Appearance","PeriodicalId":445080,"journal":{"name":"International Journal of Multimedia Data Engineering and Management","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Multimedia Data Engineering and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijmdem.2019040103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
在本文中,作者研究了位图索引对视频中出现的人脸进行时态查询。由于位图索引最初设计用于选择满足属性域中某个值的一组记录,因此对于如何将其应用于临时查询没有明确的策略。因此,作者引入了一个多层次的位图索引,作者称之为“FaceTimeMap”,用于视频中人脸的实时查询。FaceTimeMap索引的第一级用于确定一个人是否出现在视频中,而索引的第二级用于确定一个人出现的时间间隔。首先,作者分析了两个或更多的人同时出现在视频中的共同出现查询,然后研究了一个人紧接着出现在另一个人之后的下一个出现查询。此外,为了考虑人们外表之间的差距,作者研究了最终外表和先前外表的查询。查询通过在FaceTimeMap索引上应用按位操作来满足。作者提供了一些与该指数相关的性能研究。
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